A seven-gene signature and the C–C motif chemokine receptor family genes are the sarcoma-related immune genes. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Chen, Jiarui; Liang, Tuo; Cen, Jiemei; Jiang, Jie; Pan, Shixin; Huang, Shengsheng; Chen, Liyi; Sun, Xuhua; Li, Hao; Chen, Tianyou; Liang, Wei; Liao, Shian; Yu, Chaojie; Yao, Yuanlin; Ye, Zhen; Chen, Wuhua; Guo, Hao; Zhan, Xinli; Liu, Chong
• Is Part Of: Bioengineered. Volume 12:Issue 1(2021)
• Page Start: 7616
• Page End: 7630
• Publication Date: 2021-01-01
• Subjects: Sarcoma -- tumor microenvironment -- immune gene -- prognostic signature -- The Cancer Genome Atlas; Biomedical engineering -- Periodicals; Biotechnology -- Periodicals; Microbiology -- Periodicals; 660.6
• DOI: 10.1080/21655979.2021.1981797
• Languages: English
• ISSNs: 2165-5987

Abstract

ABSTRACT: Cells of the tumor microenvironment exert a vital influence on sarcoma prognosis. This study aimed to analyze and identify differentially expressed genes (DEGs) related to immunity and their significance as immune biomarkers for the accurate prediction of overall survival of patients with sarcoma. The Cancer Genome Atlas was adopted for obtaining sarcoma gene microarray and corresponding clinical information. ESTIMATE algorithm was used to calculate tumor immune microenvironment indices. Immune-associated DEGs were identified using the limma packages and were further analyzed using the ClusterProfiler package and STRING website. Based on the results of these analyses, we constructed a prognostic model. Furthermore, we assessed the prognosis prediction model through functional evaluation and analysis of GSE17674. The functional analysis revealed that the upregulated immune DEGs were related to immune-related aspects. Chemokine ligands/receptors and immune-related genes were found to be vital for sarcoma formation and progression. We established a prognostic signature of seven genes, which indicated that high-risk cases exhibit poor prognostic outcome. The prognostic signature constructed in this study can accurately predict the overall prognosis in patients with sarcoma. Moreover, the novel immune gene expression analysis may provide clinical guidance for predicting prognosis in patients with sarcoma.